Most patients with schizophrenia experience a prodrome, prior to the onset of frank illness. Measures of brain integrity during this prodromal period may reflect schizophrenia vulnerability. However, the timing of neuro- developmental alterations in schizophrenia remains unknown. Although perinatal brain insults have been implicated in the pathogenesis of schizophrenia, adolescence has also been of interest because it is during this developmental window that clinical symptoms typically arise. Several theories pose that abnormal adolescent neuromaturation underlies progression to full-blown schizophrenia. However, few studies have looked at connectivity of large-scale neural networks, or directly compared the trajectories of brain development between healthy adolescents and those at clinical high risk for developing schizophrenia (CHR). Even less research has examined the role of environmental factors such as substance use on brain development in CHR individuals. In particular, cannabis use has been identified as a potential environmental risk factor in the etiology of schizophrenia, motivating questions about how cannabis exposure might interact with brain alterations associated with the CHR phenotype. Analysis of brain network connectivity may be particularly well-suited to addressing questions concerning the neurodevelopmental trajectory associated with CHR, as well as the potential interaction of cannabis exposure on psychosis risk. The default-mode network (DMN) is a neural network that shows increased fMRI activity at rest, compared to cognitive task conditions. Prior studies of schizophrenia report associations of psychotic symptoms with hyperconnectivity of the DMN, and diffusion tensor imaging (DTI) analyses have detected poorer microstructural coherence of the fiber pathways connecting DMN regions. Together, these findings suggest that both structural and functional aspects of DMN connectivity are altered in schizophrenia, supporting a focus on the DMN's developmental trajectory in CHR individuals. Moreover, because the DMN is detectable in the absence of task performance, it is well-poised to evaluate brain-behavior relationships in developmental clinical studies, in which sizeable between-group cognitive task performance differences can complicate interpretation of traditional task-based fMRI studies. The proposed study will combine analyses of resting state fMRI with DTI in order to measure both functional and structural aspects of DMN connectivity, with a focus on examining the DMN's developmental trajectory from adolescence to adulthood in CHR and healthy comparison subjects. Further, we will examine how DMN functional and structural integrity relates to cannabis use in CHR youth. Lastly, we will examine whether DMN connectivity relates to symptom severity and predicts conversion to psychosis. Given the wide range of cognitive effects associated with the schizophrenia spectrum, a neural systems perspective may be particularly profitable in shedding light on the brain alterations underlying progression to psychosis in vulnerable individuals.